The introduction of digital technology into the field of broadcasting audiovisual signals has opened up new prospects and means that users may be offered more services.
The signals are modified during the various stages of broadcasting them because technical constraints imposed, for example in terms of bit rate or bandwidth, cause characteristic deterioration during difficult transmission conditions.
To be able to provide a quality assured service, it is necessary to develop tools and instruments for measuring the quality of the signals and, where applicable, for estimating the magnitude of the deterioration that has occurred. Many measuring methods have been developed for this purpose. Most of them are based on comparing the signal present at the input of the system under test, which is called the reference signal, with the signal obtained at the output of the system, which is called the degraded signal. Certain “reduced reference” methods compare numbers calculated for the reference signal and for the degraded signal instead of using the signal samples directly. In both cases, in order to evaluate quality by means of a comparison technique, it is necessary to synchronize the signals in time.
FIG. 1 depicts the general principle of these methods.
Although synchronization of the signals may be easily achieved in simulation or when the system under test is small, for example a coder-decoder (codec), and not geographically distributed, this is not the case in a complex system, in particular in the situation of monitoring a broadcast network. Thus the synchronization step of quality measuring algorithms is often critical.
In addition to applications for measuring quality in a broadcast network, the method described herein is applicable whenever temporal synchronization between two audio and/or video signals is required, in particular in the context of a distributed and extended system.
Various techniques may be used to synchronize digital signals in time. The objective is to establish a correspondence between a portion of the degraded signal SD and a portion of the reference signal SR. FIG. 2 depicts this in the case of two audio signals. The problem is to determine a shift DEC that will synchronize the signals.
In the case of an audio signal, the portion (or element) for which a correspondence has to be established is a time window, i.e. a period of the signal with an arbitrary duration T.
The existing methods may be divided into three classes:                Correlation approach in the time domain: This is the most usual approach and consists in comparing samples of the two audio signals SR and SD to be synchronized, based on their content. Thus the normalized intercorrelation function between SR and SD, for example, looks for the maximum resemblance over a given time period T, for example plus or minus 60 ms, i.e. a total period of 120 ms. The accuracy of synchronization obtained is potentially to the nearest sample.        Correlation approach in the time domain using marker signals: methods that use this principle seek to overcome the necessity for significant variations in the signal. To this end, a specific marker signal designed to allow robust synchronization is inserted into the audio signal SR. Thus exactly the same intercorrelation method may be applied to the marker signals extracted from the signals SR and SD to be synchronized, which in theory allows robust synchronization regardless of the content of the audio signal.        
In order to use this method, the marker signal must be inserted in such a way that the modification of the content of the audio signal is as imperceptible as possible. Several techniques may be used to insert marker signals or other specific patterns, including “watermarking”.                Synchronization using temporal markers: methods of this class are usable only if the signals are associated with temporal markers. Thus the method relies on identifying, for each marker of the reference signal, the nearest marker in the series of markers associated with the degraded signal.        
A powerful signal synchronization method is characterized by a compromise between:                its accuracy, i.e. the maximum error that occurs on synchronizing two signals (in particular, the method may be sensitive to the content of the signals),        its calculation complexity, and        finally, the volume of data necessary for effecting the synchronization.        
The main drawback of the techniques most usually employed (using the correlation approach referred to above) is the calculation power that is necessary, which becomes very high as the search period T increases (see FIG. 2). Another major drawback is the necessity for the content to evolve significantly and continuously. Depending on the type of signals analyzed, this is not always achieved. The content of the signals therefore has a direct influence on the performance of the method. Moreover, to utilize this type of approach on complete temporal signals, it is necessary to have both the signals SR and SD available at the comparison point; this is a very severe constraint that is impossible to satisfy in some applications, such as monitoring an operational broadcasting network.
A feature of the second approach (using correlation with marker signals) is the modification of the content of the audio signal resulting from inserting the marker signals, with no guarantee as to how this will impact on quality; the measurement method therefore influences the measurement itself. Regardless of the performance achieved in terms of synchronizing the two signals, this approach is not always suitable for a real quality evaluation application.
Finally, the major drawback of synchronization using temporal markers is the necessity to provide the temporal markers. Because the accuracy of the temporal markers is not always satisfactory, only a few applications are able to use a technique of this kind.
In the context of broadcast network monitoring, and because of the multiple constraints that apply to the signals transported and the multiple equipments the signals pass through (coders, multiplexers, transmultiplexers, decoders, etc.), there is no strict relationship between the audio signals and the temporal markers. Thus this solution does not achieve the necessary accuracy for a quality measuring application using a reference.